Since the invention of the printing press, the written word is the most common format by which knowledge is transferred. Computational linguistics has seen dramatic changes and some tools are very useful for applied economics and public policy research. This course will introduce students to quantitative text analysis methods and concepts and illustrate their application using examples drawn from text corpora that may be commonly used in public policy analysis, such as legislative texts or political speeches. We will work with conventional statistical and heuristic methods to summarize and compare coropra of text and extract information. However, we will also draw on a range of supervised and unsupervised machine learning methods to perform clustering and classification tasks, and illustrate their application in applied public policy research. The course will introduce students to the art of programming with R.